With the prevailing usage of
high density blade servers, the heat dissipation density of data
centers
increases exponentially. The high temperature of the data centers will
lead
to higher hardware failure costs. Improperly designed or operated data
centers may either suffer from overheated servers and potential system
failures, or from overcooled systems and paying extra utilities cost.
Minimizing the cost of operation (utilities, maintenance, device
upgrade and
replacement) of data centers is one of the key issues to optimize
computing resources and maximize business outcome.

The goal of this project is to
build a dependable, reliable sensing platform using on board sensors
and ambient sensors to collect temperature, humidity, power consumption
and computer load information. Combining this data with a heuristic
control
algorithm, we can dynamically adjust the thermal environment (by making
smarter job
scheduling decisions, by adjusting
air conditioner capacity, fan speed, frequency and voltage scaling,
etc.) to
achieve a better thermal environment, reduce the cost of operations and
improve
the business output of data centers.

In
The Press

ForbesThe Future Is Now “Dynamic
thermal
management of the data center –
Developed in conjunction with Arizona
State
University, this research
enables job scheduler software to take into account the temperature of
servers
or server blades before deciding which data center component should do
the
job. The result should be an online thermal control framework that
monitors
and manages data center thermal performance from a holistic viewpoint.
The
researchers say the challenge for the project is to make the system
reactive
so that it knows when servers are starting to fail because of heat
issues.
They say it could be another two years before this project could be
presented
to Intel as a potential product.…”

Project
Timeline

Timeline

Achievements

2005

Developed abstract heat flow model for data
center and verified with CFD simulation

Q4 2005

Developed thermal aware scheduling
based on the abstract heat flow model and verified with CFD
simulation

Q1 2006

Published a paper on thermal aware
scheduling for data centers in DASC 2006

Q2 2006

Developed a software architecture for
thermal aware acheduling for Moab
Cluster Manager and successfully demostrated the software architecture
at Research @Intel
Day using the ASU HPC datacenter